arrange_() | bind_rows_() and bind_cols_() | filter_()

Working with workflows | Models requiring

Background and Motivation | Example Usage | A basic example for a multiple linear regression | An example with a slightly more complicated model | Raw TeX code | Coefficients | Other models | Logistic Regression | Probit Regression | Ordinal Regression | Logit method | Probit method | Working with a list of models | Things the package does not yet do | Contributing

Non-standard evaluation | Referential transparency | Formula masking | Further advantages of formula masking | Computed argument name | Data-dot mechanism and bullet-list construct | Performance comparison | How to convert tidyverse code?

Messages translation | Setting first and secondary languages | Specifying language with ngettext_() | Using secondary language by default for plots and tables

Quick but versatile assertions | Base R solution with if (cond) stop() | Base R with stopifnot() | {svAssert} assertions | Assertions with | Enhanced stopifnot_() | Impact on performances | Error message translation

Meaningful error messages | Classed error messages | Message formatting | Note about warning_() | Context of error messages | Additional information with . or data-dot

Subsettable functions | Object aliasing with aka() | Data frame conversions with as_dtx() and related functions | Alternate assignment operator %<-% | Labels and units | Enhanced messages | The "data-dot" mechanism | Formula-masking and formula-select | Sections

Make better learning inline material with learnitdown | Include H5P content | Differ Shiny/learnr app loading | Selectively show details | Details | Tabs | Contextual divs | Show/hide code

Subtitle 1 | Subtitle 2 is actually quite long and could be wrapped | Title 2

Time in pastecs time series | Time units | Days | Years | So, what?

Example | Nonlinear model

Example table | Equations

Datasets in R packages | Discovering datasets in R packages | Read and write data | Metadata (label and units) | Sidecar R scripts | Reading data from URLs and cache mechanism | List of supported file formats

Formula versus aes() | The generic function chart() | chart() produces near publication-ready plots

Help | Packages | Analyses in batch and show progression | Capture and parse R code | Encode/decode R objects in Rjson | Get system file or directory | Various information functions | Miscellaneous

Introduction | Unit testing in R without 'svUnit' | Unit testing framework for R with 'svUnit' | Installation | Overview of 'svUnit' | Assertions in 'svUnit' | Manipulating the logger data | Test function | Test units | Test suites: collections of test functions and units | Using 'svUnit' with RStudio | Using 'svUnit' with SciViews Komodo | References

Setup | Unconditional models | Models with predictors at level 1 | Models with unstructured variance-covariance specifications | Group level predictors | Interactions | Alternative variance-covariance specifications | Using estimated coefficients | Future developments

Introduction | {chart} for {ggplot2} users

Flow objects to test alternate scenarios | Visual map of Flow objects inheritance

Using Tcl/Tk dialog boxes in a custom GUI

Central location for GUI information and status | Inactivate modal dialog boxes | GUI management and examples

Implementing a client | Callback argument | Utilities on the server-side | Alternate solutions

Quick install and use | Lower-level interaction | Configuration and special instructions | Disconnection

Display equations from an R chunk | Inline equations in R Markdown or Quarto documents | Display equations with labels | Customizing equations

Changing variable names | Current models and future plans

Coverage | Unit Tests

Basic Examples | ARIMA without Exogenous Regressors | Setup | Extracting the equation | Regression with ARIMA Errors | Working with other parts of | Future Development

A simple use case | Base graphics | More complicated: Multi-line equations | Convert to a single line | Manually place text geoms | Limitations and future development

TL;DR | More detail

The pcomp object

Pure, predictable, pipeable, ... and data-aware | Choice of the name | A simpler and more efficient pipe operator? | Mixing Pipe() and proto(): the Flow object